Research Assistant, Metabolism and Basic Biology of Aging

Research Assistant Position Research in our Metabolism & Basic Biology of Aging directive focuses on understanding cellular and molecular processes that contribute to age-related diseases. Scientists in this directive investigate a variety of factors including dietary components, physical activity, immune responses, intestinal homeostasis, the microbiome, cellular dysfunction, and senescence, and the key metabolic and molecular processes by which those factors impact age-related health. The department applies comparative, evolutionary, and systems biology approaches to reveal modulators of life history trait variation within and across species. This is a limited term position with an end date of September 30, 2027. This is also a grant funded position and is not eligible for severance pay. In collaboration with the Principal Investigator and Postdoctoral Scholar, the Research Assistant will conduct research into the genomic basis of lifespan variation across vertebrates. This will initially involve bioinformatic and computational tool development and deployment, but could also lead to wet-lab experimental work including transgenic expression assays and comparative transcriptomics/metabolomics. Conduct bioinformatic and computational analyses in R and Python, with reproducible and interpretable code pipelines and documentation. Read and synthesize literature on comparative genomics, as well as comparative studies of longevity-promoting mechanisms across animals. Clear communication and documentation, including daily check-ins with post-doctoral mentor and weekly check-ins with PI.Review results and suggest modifications to experiments and protocols where necessary. Create, refine/edit and update research protocols. Assistance with manuscript writing, as appropriate. Active participation in weekly lab meetings and journal club meetings. Bench work validating findings and other lab work as directed by PIKnowledge and experience typically acquired by: Bachelor's degree in science and 3-5 years of related laboratory experience OR Master's degree and up to one year laboratory experience Familiarity with coding and bioinformatic analysis in R and/or Python Demonstrated interest in ecology or evolution and longevity research is preferred.